Optimality and convergence for convex ensemble learning with sparsity and diversity based on fixed point optimization
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.07.046
Abstract: Abstract This paper discusses the classifier ensemble problem with sparsity and diversity learning, which is a central issue in machine learning. The current approach for reducing the size and increasing the accuracy of a classifier… read more here.
Keywords: sparsity diversity; classifier ensemble; problem; fixed point ... See more keywords
Automatic Recommendation Method for Classifier Ensemble Structure Using Meta-Learning
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DOI: 10.1109/access.2021.3099689
Abstract: Machine Learning (ML) is a field that aims to develop efficient techniques to provide intelligent decision making solutions to complex real problems. Among the different ML structures, a classifier ensemble has been successfully applied to… read more here.
Keywords: classifier ensemble; automatic recommendation; structure using; structure ... See more keywords
Multicriteria Classifier Ensemble Learning for Imbalanced Data
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DOI: 10.1109/access.2022.3149914
Abstract: One of the vital problems with the imbalanced data classifier training is the definition of an optimization criterion. Typically, since the exact cost of misclassification of the individual classes is unknown, combined metrics and loss… read more here.
Keywords: multicriteria classifier; criterion; learning imbalanced; imbalanced data ... See more keywords
Classifier Ensemble by Exploring Supplementary Ordering Information
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2018.2818138
Abstract: Supplementary information has been proven to be particularly useful in many machine learning tasks. In ensemble learning for a set of trained base classifiers, there also exists abundant implicit supplementary information about the performance orderings… read more here.
Keywords: classifier ensemble; information; supplementary information; ordering information ... See more keywords
A Novel Classifier Ensemble Method Based on Subspace Enhancement for High-Dimensional Data Classification
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2021.3087517
Abstract: High-dimensional small-size data seriously affects the performance of classifiers. By combining classifiers, ensemble learning obtains higher accuracy and more robust predictions. However, these classifier ensemble methods suffer from several limitations: 1) ensemble with sample space… read more here.
Keywords: subspace enhancement; classifier ensemble; feature; dimensional data ... See more keywords
Hybrid Classifier Ensemble for Imbalanced Data
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2019.2920246
Abstract: The class imbalance problem has become a leading challenge. Although conventional imbalance learning methods are proposed to tackle this problem, they have some limitations: 1) undersampling methods suffer from losing important information and 2) cost-sensitive… read more here.
Keywords: classifier ensemble; imbalance; ensemble imbalanced; problem ... See more keywords
Classifier Ensemble Based on Multiview Optimization for High-Dimensional Imbalanced Data Classification.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3177695
Abstract: High-dimensional class imbalanced data have plagued the performance of classification algorithms seriously. Because of a large number of redundant/invalid features and the class imbalanced issue, it is difficult to construct an optimal classifier for high-dimensional… read more here.
Keywords: classification; dimensional imbalanced; classifier ensemble; multiview optimization ... See more keywords
Semantic relational machine learning model for sentiment analysis using cascade feature selection and heterogeneous classifier ensemble
Sign Up to like & getrecommendations! Published in 2022 at "PeerJ Computer Science"
DOI: 10.7717/peerj-cs.1100
Abstract: The exponential rise in social media via microblogging sites like Twitter has sparked curiosity in sentiment analysis that exploits user feedback towards a targeted product or service. Considering its significance in business intelligence and decision-making,… read more here.
Keywords: feature; classifier; sentiment analysis; classifier ensemble ... See more keywords